The Atlantic has gone through the gruesome process of figuring out how Netflix comes up with "specific genres that it suggests to you," like the Foreign Satanic Stories from the 1980s. It turns out that Netflix "has meticulously analyzed and tagged every movie and TV show imaginable" and currently has "76,897 unique ways to describe types of movies." This part is amazing:
Netflix cooperated with my quest to understand what they internally call "altgenres," and made VP of product innovation Todd Yellin, the man who conceived of the system, available for an in-depth interview. Georgia Tech professor and Atlantic contributing editor, Ian Bogost, worked closely with me recreating the Netflix grammar, and he programmed the magical genre generator above.
If we reverse engineered Yellin's system, it was Yellin himself who imagined a much more ambitious reverse-engineering process. Using large teams of people specially trained to watch movies, Netflix deconstructed Hollywood. They paid people to watch films and tag them with all kinds of metadata. This process is so sophisticated and precise that taggers receive a 36-page training document that teaches them how to rate movies on their sexually suggestive content, goriness, romance levels, and even narrative elements like plot conclusiveness.
They capture dozens of different movie attributes. They even rate the moral status of characters. When these tags are combined with millions of users viewing habits, they become Netflix's competitive advantage. The company's main goal as a business is to gain and retain subscribers. And the genres that it displays to people are a key part of that strategy. "Members connect with these [genre] rows so well that we measure an increase in member retention by placing the most tailored rows higher on the page instead of lower," the company revealed in a 2012 blog post. The better Netflix shows that it knows you, the likelier you are to stick around.
And now, they have a terrific advantage in their efforts to produce their own content: Netflix has created a database of American cinematic predilections. The data can't tell them how to make a TV show, but it can tell them what they should be making. When they create a show like House of Cards, they aren't guessing at what people want.
The hilarious image you see above is from Darth.
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